{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>x4</th>\n",
       "      <th>x5</th>\n",
       "      <th>x6</th>\n",
       "      <th>x7</th>\n",
       "      <th>x8</th>\n",
       "      <th>x9</th>\n",
       "      <th>x10</th>\n",
       "      <th>x11</th>\n",
       "      <th>x12</th>\n",
       "      <th>x13</th>\n",
       "      <th>y</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3831732</td>\n",
       "      <td>181.54</td>\n",
       "      <td>448.19</td>\n",
       "      <td>7571.00</td>\n",
       "      <td>6212.70</td>\n",
       "      <td>6370241</td>\n",
       "      <td>525.71</td>\n",
       "      <td>985.31</td>\n",
       "      <td>60.62</td>\n",
       "      <td>65.66</td>\n",
       "      <td>120.0</td>\n",
       "      <td>1.029</td>\n",
       "      <td>5321</td>\n",
       "      <td>64.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3913824</td>\n",
       "      <td>214.63</td>\n",
       "      <td>549.97</td>\n",
       "      <td>9038.16</td>\n",
       "      <td>7601.73</td>\n",
       "      <td>6467115</td>\n",
       "      <td>618.25</td>\n",
       "      <td>1259.20</td>\n",
       "      <td>73.46</td>\n",
       "      <td>95.46</td>\n",
       "      <td>113.5</td>\n",
       "      <td>1.051</td>\n",
       "      <td>6529</td>\n",
       "      <td>99.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3928907</td>\n",
       "      <td>239.56</td>\n",
       "      <td>686.44</td>\n",
       "      <td>9905.31</td>\n",
       "      <td>8092.82</td>\n",
       "      <td>6560508</td>\n",
       "      <td>638.94</td>\n",
       "      <td>1468.06</td>\n",
       "      <td>81.16</td>\n",
       "      <td>81.16</td>\n",
       "      <td>108.2</td>\n",
       "      <td>1.064</td>\n",
       "      <td>7008</td>\n",
       "      <td>88.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4282130</td>\n",
       "      <td>261.58</td>\n",
       "      <td>802.59</td>\n",
       "      <td>10444.60</td>\n",
       "      <td>8767.98</td>\n",
       "      <td>6664862</td>\n",
       "      <td>656.58</td>\n",
       "      <td>1678.12</td>\n",
       "      <td>85.72</td>\n",
       "      <td>91.70</td>\n",
       "      <td>102.2</td>\n",
       "      <td>1.092</td>\n",
       "      <td>7694</td>\n",
       "      <td>106.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4453911</td>\n",
       "      <td>283.14</td>\n",
       "      <td>904.57</td>\n",
       "      <td>11255.70</td>\n",
       "      <td>9422.33</td>\n",
       "      <td>6741400</td>\n",
       "      <td>758.83</td>\n",
       "      <td>1893.52</td>\n",
       "      <td>88.88</td>\n",
       "      <td>114.61</td>\n",
       "      <td>97.7</td>\n",
       "      <td>1.200</td>\n",
       "      <td>8027</td>\n",
       "      <td>137.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4548852</td>\n",
       "      <td>308.58</td>\n",
       "      <td>1000.69</td>\n",
       "      <td>12018.52</td>\n",
       "      <td>9751.44</td>\n",
       "      <td>6850024</td>\n",
       "      <td>878.26</td>\n",
       "      <td>2139.18</td>\n",
       "      <td>92.85</td>\n",
       "      <td>152.78</td>\n",
       "      <td>98.5</td>\n",
       "      <td>1.198</td>\n",
       "      <td>8549</td>\n",
       "      <td>188.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4962579</td>\n",
       "      <td>348.09</td>\n",
       "      <td>1121.13</td>\n",
       "      <td>13966.53</td>\n",
       "      <td>11349.47</td>\n",
       "      <td>7006896</td>\n",
       "      <td>923.67</td>\n",
       "      <td>2492.74</td>\n",
       "      <td>94.37</td>\n",
       "      <td>170.62</td>\n",
       "      <td>102.8</td>\n",
       "      <td>1.348</td>\n",
       "      <td>9566</td>\n",
       "      <td>219.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5029338</td>\n",
       "      <td>387.81</td>\n",
       "      <td>1248.29</td>\n",
       "      <td>14694.00</td>\n",
       "      <td>11467.35</td>\n",
       "      <td>7125979</td>\n",
       "      <td>978.21</td>\n",
       "      <td>2841.65</td>\n",
       "      <td>97.28</td>\n",
       "      <td>214.53</td>\n",
       "      <td>98.9</td>\n",
       "      <td>1.467</td>\n",
       "      <td>10473</td>\n",
       "      <td>271.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5070216</td>\n",
       "      <td>453.49</td>\n",
       "      <td>1370.68</td>\n",
       "      <td>13380.47</td>\n",
       "      <td>10671.78</td>\n",
       "      <td>7206229</td>\n",
       "      <td>1009.24</td>\n",
       "      <td>3203.96</td>\n",
       "      <td>103.07</td>\n",
       "      <td>202.18</td>\n",
       "      <td>97.6</td>\n",
       "      <td>1.560</td>\n",
       "      <td>11469</td>\n",
       "      <td>269.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>5210706</td>\n",
       "      <td>533.55</td>\n",
       "      <td>1494.27</td>\n",
       "      <td>15002.59</td>\n",
       "      <td>11570.58</td>\n",
       "      <td>7251888</td>\n",
       "      <td>1175.17</td>\n",
       "      <td>3758.62</td>\n",
       "      <td>109.91</td>\n",
       "      <td>222.51</td>\n",
       "      <td>100.1</td>\n",
       "      <td>1.456</td>\n",
       "      <td>12360</td>\n",
       "      <td>300.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5407087</td>\n",
       "      <td>598.33</td>\n",
       "      <td>1677.77</td>\n",
       "      <td>16884.16</td>\n",
       "      <td>13120.83</td>\n",
       "      <td>7376720</td>\n",
       "      <td>1348.93</td>\n",
       "      <td>4450.55</td>\n",
       "      <td>117.15</td>\n",
       "      <td>249.01</td>\n",
       "      <td>101.7</td>\n",
       "      <td>1.424</td>\n",
       "      <td>14174</td>\n",
       "      <td>338.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5744550</td>\n",
       "      <td>665.32</td>\n",
       "      <td>1905.84</td>\n",
       "      <td>18287.24</td>\n",
       "      <td>14468.24</td>\n",
       "      <td>7505322</td>\n",
       "      <td>1519.16</td>\n",
       "      <td>5154.23</td>\n",
       "      <td>130.22</td>\n",
       "      <td>303.41</td>\n",
       "      <td>101.5</td>\n",
       "      <td>1.456</td>\n",
       "      <td>16394</td>\n",
       "      <td>408.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5994973</td>\n",
       "      <td>738.97</td>\n",
       "      <td>2199.14</td>\n",
       "      <td>19850.66</td>\n",
       "      <td>15444.93</td>\n",
       "      <td>7607220</td>\n",
       "      <td>1696.38</td>\n",
       "      <td>6081.86</td>\n",
       "      <td>128.51</td>\n",
       "      <td>356.99</td>\n",
       "      <td>102.3</td>\n",
       "      <td>1.438</td>\n",
       "      <td>17881</td>\n",
       "      <td>476.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>6236312</td>\n",
       "      <td>877.07</td>\n",
       "      <td>2624.24</td>\n",
       "      <td>22469.22</td>\n",
       "      <td>18951.32</td>\n",
       "      <td>7734787</td>\n",
       "      <td>1863.34</td>\n",
       "      <td>7140.32</td>\n",
       "      <td>149.87</td>\n",
       "      <td>429.36</td>\n",
       "      <td>103.4</td>\n",
       "      <td>1.474</td>\n",
       "      <td>20058</td>\n",
       "      <td>838.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6529045</td>\n",
       "      <td>1005.37</td>\n",
       "      <td>3187.39</td>\n",
       "      <td>25316.72</td>\n",
       "      <td>20835.95</td>\n",
       "      <td>7841695</td>\n",
       "      <td>2105.54</td>\n",
       "      <td>8287.38</td>\n",
       "      <td>169.19</td>\n",
       "      <td>508.84</td>\n",
       "      <td>105.9</td>\n",
       "      <td>1.515</td>\n",
       "      <td>22114</td>\n",
       "      <td>843.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>6791495</td>\n",
       "      <td>1118.03</td>\n",
       "      <td>3615.77</td>\n",
       "      <td>27609.59</td>\n",
       "      <td>22820.89</td>\n",
       "      <td>7946154</td>\n",
       "      <td>2659.85</td>\n",
       "      <td>9138.21</td>\n",
       "      <td>172.28</td>\n",
       "      <td>557.74</td>\n",
       "      <td>97.5</td>\n",
       "      <td>1.633</td>\n",
       "      <td>24190</td>\n",
       "      <td>1107.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>7110695</td>\n",
       "      <td>1304.48</td>\n",
       "      <td>4476.38</td>\n",
       "      <td>30658.49</td>\n",
       "      <td>25011.61</td>\n",
       "      <td>8061370</td>\n",
       "      <td>3263.57</td>\n",
       "      <td>10748.28</td>\n",
       "      <td>188.57</td>\n",
       "      <td>664.06</td>\n",
       "      <td>103.2</td>\n",
       "      <td>1.638</td>\n",
       "      <td>29549</td>\n",
       "      <td>1399.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7431755</td>\n",
       "      <td>1700.87</td>\n",
       "      <td>5243.03</td>\n",
       "      <td>34438.08</td>\n",
       "      <td>28209.74</td>\n",
       "      <td>8145797</td>\n",
       "      <td>3412.21</td>\n",
       "      <td>12423.44</td>\n",
       "      <td>204.54</td>\n",
       "      <td>710.66</td>\n",
       "      <td>105.5</td>\n",
       "      <td>1.670</td>\n",
       "      <td>34214</td>\n",
       "      <td>1535.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>7512997</td>\n",
       "      <td>1969.51</td>\n",
       "      <td>5977.27</td>\n",
       "      <td>38053.52</td>\n",
       "      <td>30490.44</td>\n",
       "      <td>8222969</td>\n",
       "      <td>3758.39</td>\n",
       "      <td>13551.21</td>\n",
       "      <td>213.76</td>\n",
       "      <td>760.49</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.825</td>\n",
       "      <td>37934</td>\n",
       "      <td>1579.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>7599295</td>\n",
       "      <td>2110.78</td>\n",
       "      <td>6882.85</td>\n",
       "      <td>42049.14</td>\n",
       "      <td>33156.83</td>\n",
       "      <td>8323096</td>\n",
       "      <td>4454.55</td>\n",
       "      <td>15420.14</td>\n",
       "      <td>228.46</td>\n",
       "      <td>852.56</td>\n",
       "      <td>102.6</td>\n",
       "      <td>1.906</td>\n",
       "      <td>41972</td>\n",
       "      <td>2088.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "         x1       x2       x3        x4        x5       x6       x7        x8  \\\n",
       "0   3831732   181.54   448.19   7571.00   6212.70  6370241   525.71    985.31   \n",
       "1   3913824   214.63   549.97   9038.16   7601.73  6467115   618.25   1259.20   \n",
       "2   3928907   239.56   686.44   9905.31   8092.82  6560508   638.94   1468.06   \n",
       "3   4282130   261.58   802.59  10444.60   8767.98  6664862   656.58   1678.12   \n",
       "4   4453911   283.14   904.57  11255.70   9422.33  6741400   758.83   1893.52   \n",
       "5   4548852   308.58  1000.69  12018.52   9751.44  6850024   878.26   2139.18   \n",
       "6   4962579   348.09  1121.13  13966.53  11349.47  7006896   923.67   2492.74   \n",
       "7   5029338   387.81  1248.29  14694.00  11467.35  7125979   978.21   2841.65   \n",
       "8   5070216   453.49  1370.68  13380.47  10671.78  7206229  1009.24   3203.96   \n",
       "9   5210706   533.55  1494.27  15002.59  11570.58  7251888  1175.17   3758.62   \n",
       "10  5407087   598.33  1677.77  16884.16  13120.83  7376720  1348.93   4450.55   \n",
       "11  5744550   665.32  1905.84  18287.24  14468.24  7505322  1519.16   5154.23   \n",
       "12  5994973   738.97  2199.14  19850.66  15444.93  7607220  1696.38   6081.86   \n",
       "13  6236312   877.07  2624.24  22469.22  18951.32  7734787  1863.34   7140.32   \n",
       "14  6529045  1005.37  3187.39  25316.72  20835.95  7841695  2105.54   8287.38   \n",
       "15  6791495  1118.03  3615.77  27609.59  22820.89  7946154  2659.85   9138.21   \n",
       "16  7110695  1304.48  4476.38  30658.49  25011.61  8061370  3263.57  10748.28   \n",
       "17  7431755  1700.87  5243.03  34438.08  28209.74  8145797  3412.21  12423.44   \n",
       "18  7512997  1969.51  5977.27  38053.52  30490.44  8222969  3758.39  13551.21   \n",
       "19  7599295  2110.78  6882.85  42049.14  33156.83  8323096  4454.55  15420.14   \n",
       "\n",
       "        x9     x10    x11    x12    x13        y  \n",
       "0    60.62   65.66  120.0  1.029   5321    64.87  \n",
       "1    73.46   95.46  113.5  1.051   6529    99.75  \n",
       "2    81.16   81.16  108.2  1.064   7008    88.11  \n",
       "3    85.72   91.70  102.2  1.092   7694   106.07  \n",
       "4    88.88  114.61   97.7  1.200   8027   137.32  \n",
       "5    92.85  152.78   98.5  1.198   8549   188.14  \n",
       "6    94.37  170.62  102.8  1.348   9566   219.91  \n",
       "7    97.28  214.53   98.9  1.467  10473   271.91  \n",
       "8   103.07  202.18   97.6  1.560  11469   269.10  \n",
       "9   109.91  222.51  100.1  1.456  12360   300.55  \n",
       "10  117.15  249.01  101.7  1.424  14174   338.45  \n",
       "11  130.22  303.41  101.5  1.456  16394   408.86  \n",
       "12  128.51  356.99  102.3  1.438  17881   476.72  \n",
       "13  149.87  429.36  103.4  1.474  20058   838.99  \n",
       "14  169.19  508.84  105.9  1.515  22114   843.14  \n",
       "15  172.28  557.74   97.5  1.633  24190  1107.67  \n",
       "16  188.57  664.06  103.2  1.638  29549  1399.16  \n",
       "17  204.54  710.66  105.5  1.670  34214  1535.14  \n",
       "18  213.76  760.49  103.0  1.825  37934  1579.68  \n",
       "19  228.46  852.56  102.6  1.906  41972  2088.14  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#-*- coding:utf-8 -*-\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "inputfile1 = 'data1.csv'\n",
    "data = pd.read_csv(inputfile1)\n",
    "data # 1994到2013年间的各个影响因素的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Min</th>\n",
       "      <th>Max</th>\n",
       "      <th>Mean</th>\n",
       "      <th>Std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>x1</th>\n",
       "      <td>3831732.00</td>\n",
       "      <td>7599295.00</td>\n",
       "      <td>5579519.95</td>\n",
       "      <td>1262194.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x2</th>\n",
       "      <td>181.54</td>\n",
       "      <td>2110.78</td>\n",
       "      <td>765.04</td>\n",
       "      <td>595.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x3</th>\n",
       "      <td>448.19</td>\n",
       "      <td>6882.85</td>\n",
       "      <td>2370.83</td>\n",
       "      <td>1919.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x4</th>\n",
       "      <td>7571.00</td>\n",
       "      <td>42049.14</td>\n",
       "      <td>19644.69</td>\n",
       "      <td>10203.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x5</th>\n",
       "      <td>6212.70</td>\n",
       "      <td>33156.83</td>\n",
       "      <td>15870.95</td>\n",
       "      <td>8199.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x6</th>\n",
       "      <td>6370241.00</td>\n",
       "      <td>8323096.00</td>\n",
       "      <td>7350513.60</td>\n",
       "      <td>621341.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x7</th>\n",
       "      <td>525.71</td>\n",
       "      <td>4454.55</td>\n",
       "      <td>1712.24</td>\n",
       "      <td>1184.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x8</th>\n",
       "      <td>985.31</td>\n",
       "      <td>15420.14</td>\n",
       "      <td>5705.80</td>\n",
       "      <td>4478.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x9</th>\n",
       "      <td>60.62</td>\n",
       "      <td>228.46</td>\n",
       "      <td>129.49</td>\n",
       "      <td>50.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x10</th>\n",
       "      <td>65.66</td>\n",
       "      <td>852.56</td>\n",
       "      <td>340.22</td>\n",
       "      <td>251.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x11</th>\n",
       "      <td>97.50</td>\n",
       "      <td>120.00</td>\n",
       "      <td>103.31</td>\n",
       "      <td>5.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x12</th>\n",
       "      <td>1.03</td>\n",
       "      <td>1.91</td>\n",
       "      <td>1.42</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x13</th>\n",
       "      <td>5321.00</td>\n",
       "      <td>41972.00</td>\n",
       "      <td>17273.80</td>\n",
       "      <td>11109.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>64.87</td>\n",
       "      <td>2088.14</td>\n",
       "      <td>618.08</td>\n",
       "      <td>609.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Min         Max        Mean         Std\n",
       "x1   3831732.00  7599295.00  5579519.95  1262194.72\n",
       "x2       181.54     2110.78      765.04      595.70\n",
       "x3       448.19     6882.85     2370.83     1919.17\n",
       "x4      7571.00    42049.14    19644.69    10203.02\n",
       "x5      6212.70    33156.83    15870.95     8199.77\n",
       "x6   6370241.00  8323096.00  7350513.60   621341.85\n",
       "x7       525.71     4454.55     1712.24     1184.71\n",
       "x8       985.31    15420.14     5705.80     4478.40\n",
       "x9        60.62      228.46      129.49       50.51\n",
       "x10       65.66      852.56      340.22      251.58\n",
       "x11       97.50      120.00      103.31        5.51\n",
       "x12        1.03        1.91        1.42        0.25\n",
       "x13     5321.00    41972.00    17273.80    11109.19\n",
       "y         64.87     2088.14      618.08      609.25"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ---------------* 1_1summaryMeasure *---------------\n",
    "# 概括性分析描述性统计\n",
    "r = [data.min(), data.max(), data.mean(), data.std()] #统计最小、最大、平均、标准差\n",
    "r = pd.DataFrame(r, index= ['Min', 'Max', 'Mean', 'Std']).T #计算相关系数矩阵\n",
    "result = np.round(r, 2) # 保留两位小数  （***）\n",
    "# np.round(data.describe().T[['min', 'max', 'mean', 'std']],2) # 等价于上面数据探索\n",
    "#保存的表名命名格式为“1_k此表功能名称”，是此小节生成的第1张表格，功能为summaryMeasure：概括性分析描述性统计\n",
    "result.to_excel('1_1summaryMeasure.xlsx')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
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       "      <th>x4</th>\n",
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       "      <th>x1</th>\n",
       "      <td>1.00</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
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       "    <tr>\n",
       "      <th>x3</th>\n",
       "      <td>0.95</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>0.89</td>\n",
       "      <td>1.00</td>\n",
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       "    <tr>\n",
       "      <th>x4</th>\n",
       "      <td>0.97</td>\n",
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       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
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       "    <tr>\n",
       "      <th>x5</th>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x6</th>\n",
       "      <td>0.99</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.96</td>\n",
       "      <td>-0.34</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.91</td>\n",
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       "    <tr>\n",
       "      <th>x7</th>\n",
       "      <td>0.95</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>0.89</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x8</th>\n",
       "      <td>0.97</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
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       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
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       "    <tr>\n",
       "      <th>x9</th>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>-0.23</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x10</th>\n",
       "      <td>0.98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.96</td>\n",
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       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x11</th>\n",
       "      <td>-0.29</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.19</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>-0.34</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.23</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x12</th>\n",
       "      <td>0.94</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.90</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x13</th>\n",
       "      <td>0.96</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.94</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>0.90</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>0.94</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.99</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       x1    x2    x3    x4    x5    x6    x7    x8    x9   x10   x11   x12  \\\n",
       "x1   1.00  0.95  0.95  0.97  0.97  0.99  0.95  0.97  0.98  0.98 -0.29  0.94   \n",
       "x2   0.95  1.00  1.00  0.99  0.99  0.92  0.99  0.99  0.98  0.98 -0.13  0.89   \n",
       "x3   0.95  1.00  1.00  0.99  0.99  0.92  1.00  0.99  0.98  0.99 -0.15  0.89   \n",
       "x4   0.97  0.99  0.99  1.00  1.00  0.95  0.99  1.00  0.99  1.00 -0.19  0.91   \n",
       "x5   0.97  0.99  0.99  1.00  1.00  0.95  0.99  1.00  0.99  1.00 -0.18  0.90   \n",
       "x6   0.99  0.92  0.92  0.95  0.95  1.00  0.93  0.95  0.97  0.96 -0.34  0.95   \n",
       "x7   0.95  0.99  1.00  0.99  0.99  0.93  1.00  0.99  0.98  0.99 -0.15  0.89   \n",
       "x8   0.97  0.99  0.99  1.00  1.00  0.95  0.99  1.00  0.99  1.00 -0.15  0.90   \n",
       "x9   0.98  0.98  0.98  0.99  0.99  0.97  0.98  0.99  1.00  0.99 -0.23  0.91   \n",
       "x10  0.98  0.98  0.99  1.00  1.00  0.96  0.99  1.00  0.99  1.00 -0.17  0.90   \n",
       "x11 -0.29 -0.13 -0.15 -0.19 -0.18 -0.34 -0.15 -0.15 -0.23 -0.17  1.00 -0.43   \n",
       "x12  0.94  0.89  0.89  0.91  0.90  0.95  0.89  0.90  0.91  0.90 -0.43  1.00   \n",
       "x13  0.96  1.00  1.00  1.00  0.99  0.94  1.00  1.00  0.99  0.99 -0.16  0.90   \n",
       "y    0.94  0.98  0.99  0.99  0.99  0.91  0.99  0.99  0.98  0.99 -0.12  0.87   \n",
       "\n",
       "      x13     y  \n",
       "x1   0.96  0.94  \n",
       "x2   1.00  0.98  \n",
       "x3   1.00  0.99  \n",
       "x4   1.00  0.99  \n",
       "x5   0.99  0.99  \n",
       "x6   0.94  0.91  \n",
       "x7   1.00  0.99  \n",
       "x8   1.00  0.99  \n",
       "x9   0.99  0.98  \n",
       "x10  0.99  0.99  \n",
       "x11 -0.16 -0.12  \n",
       "x12  0.90  0.87  \n",
       "x13  1.00  0.99  \n",
       "y    0.99  1.00  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ---------------* 1_2relatedAnalysis *---------------\n",
    "\n",
    "# 计算各个变量之间的皮尔森系数'pearson'/ 'kendall'/ 'spearman'\n",
    "result1 = np.round(data.corr(method='pearson'), 2)\n",
    "#保存的表名命名格式为“1_k此表功能名称”，是此小节生成的第2张表格，功能为relatedAnalysis：相关性分析\n",
    "result1.to_csv(\"1_2relatedAnalysis.csv\")\n",
    "result1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from scipy import stats\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rklwzbCQAYCrWj2u4kiTdfUGSY0mOJrm8uy8aOhQAwDLZceCqqiuT7E9yIMnB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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc63bd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrmat = data.corr()\n",
    "f, ax = plt.subplots(figsize=(12, 9))\n",
    "sns.heatmap(corrmat, vmax=.8, square=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
